{"id":"W1604934725","doi":"","title":"Interacting with big interfaces on small screens: a comparison of fisheye, zoom, and panning techniques","year":2004,"lang":"en","type":"article","venue":"","topic":"Interactive and Immersive Displays","field":"Computer Science","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Panning (audio); Zoom; Computer science; Task (project management); Mobile device; Software; User interface; Scrolling; Computer graphics (images); Display size; Interface (matter); Human–computer interaction; Computer vision; Artificial intelligence; Display device; Operating system; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009984411,0.0001451184,0.0002116627,0.000149613,0.00007046346,0.00009160338,0.0003177095,0.00003544022,0.000005752789],"category_scores_gemma":[0.00004786539,0.0001059808,0.00003071996,0.0001624608,0.00005646583,0.0003855371,0.0001765144,0.0001893186,0.000005976522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000317989,"about_ca_system_score_gemma":0.00002396943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003421351,"about_ca_topic_score_gemma":0.0001058191,"domain_scores_codex":[0.9991608,0.00002690472,0.0002128348,0.0002931895,0.0001262016,0.0001801157],"domain_scores_gemma":[0.9992956,0.0001535682,0.0001592546,0.0002204108,0.0001302187,0.00004095652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007780743,0.001294258,0.04582497,0.0002067418,0.0003784944,0.00006232507,0.03025744,0.0004898562,0.599624,0.07036566,0.001264852,0.2494533],"study_design_scores_gemma":[0.0002905424,0.001345413,0.003941612,0.0006946178,0.000007348227,0.00001802925,0.002350742,0.001137823,0.9895988,0.0001496399,0.0002876928,0.0001777919],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5365495,0.00003461147,0.4467359,0.0004367441,0.00008555687,0.0001333423,9.591973e-7,0.00004596944,0.01597749],"genre_scores_gemma":[0.9594393,0.000003725549,0.04011247,0.0003442489,0.00001855611,0.000006195847,0.000001009017,0.000007424976,0.00006710256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4228898,"threshold_uncertainty_score":0.432177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03696868519383856,"score_gpt":0.2919094070387256,"score_spread":0.254940721844887,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}